Universitat Oberta de Catalunya
Universitat Autònoma de Barcelona
Despite there is a wide interest in climate change mitigation (Andre et al. 2024; Falkner 2016; Mayer, Shames, and Wronski 2017), global coverage surveys only began in recent years; e.g. WRP (2019), PCV (2021).
We aim to harmonize disparate survey data on climate attitudes into a single, comparable latent measure. With this is mind, we will generate three complementary datasets:
Figure 1: Global coverage of climate change attitude survey data (2010–2024)
Figure 2: Country-year climate change attitudes data coverage (2010–2024)
Items can represent different dimensions of CC support.
Figure 3: Parallel analysis scree plot for PCA (27 items; N > 40)
Item selection criteria:
Bayesian ordinal Item Response Theory (IRT) with partial pooling (e.g. Claassen 2019).
167 countries; world GDP (99.5%); population (98.6%).
Reasonably balanced: 60%-60% dem, 24k-18k GDPcap.
Nearly 72 countries (57% global GDP, 28% pop).
Unbalanced: 70%-40% democracies, 31k-13k GDPc
Nearly 50 countries.
Unbalanced: Primarily OECD, democracies and high GDPc.
This research presents a harmonized and globally representative dataset of public attitudes toward climate change.
Applies a Bayesian ordinal IRT model to estimate a latent measure of climate support across countries and years.
Outputs three complementary datasets.
European Political Science Association - Madrid 2025